Spread spectrum Code Division Multiple Access (CDMA) systems are characterized by transmission of information over a radio frequency bandwidth much larger than that normally used in narrowband radio systems. This is achieved using a pseudorandom sequence to effect the RF-spreading which is shared by the transmitter and receiver, and the use of unique orthogonal random sequences to differentiate between users sharing the same RF-channel bandwidth. Specifically, CDMA is one of the technologies being used in the United States for the 800 MHz cellular bands and the 1900 MHz PCS bands. It differs from analog cellular and D-AMPS/GSM systems in the respect that users are differentiated from each other by the unique code (i.e. orthogonal code) rather than frequency assignment as in AMPS, or frequency and time slot assignment as in GSM and D-AMPS.
The CDMA systems are standardized according to TIA/EIA/IS-95(Mobile Station-Base Station Compatibility Standard for Dual Mode Wideband Spread Spectrum Cellular System-1992 or its latest revision). In the IS-95 version of CDMA, each signal is a different and mutualy orthogonal pseudorandom binary sequence that modulates the carrier and spreads the spectrum of the carrier frequency. Operation of an IS-95 CDMA cellular system can be characterized by the interrelationship among three variables.
The variables are Quality, Capacity and Range (QCR). These three variables can be optimized individually. However, if this is done then the other two variables would likely be unsatisfactory. The CDMA system must be operated such that all three variables are set in a manner to provide sufficient capacity, good quality and adequate coverage i.e. range. The overall performance of all three variables is also dependent on the protocol/modulation scheme which is used and, the specific implementation of the software and hardware of the mobile unit and cellular system. The former has already been standardized and cannot be changed; the latter is the focus of the testing, analysis, and optimization system and technique of the present invention.
The foregoing inter-relationship between the three variables can be expressed as follows: EQU A*Q+b*C+c*R=K
Where a, b, c are constants
Q=a Quality Measurement (ex. 1=MOS 1; MOS=Mean Opinion Score) PA1 C=a Capacity Measurement (ex. 1=Analog Capacity) PA1 R=Range in Meters PA1 K is a constant for a particular implementation which may change depending on which hardware and software is used.
From this mathematical expression it can be seen that in CDMA the previously indicated variables can be utilized to either adjust the system or capacity or increase the range at a reduced capacity (i.e. number of users), or to increase capacity over reduced range. Alternatively, it is possible to reduce quality and increase range or capacity or possibly both,due to the multivariate system behavior. To summarize, the deployment of an IS-95 CDMA Cellular System requires that many software/hardware elements of the system mesh and operate well together. Consequently, in order to obtain the required quality, capacity and range (QCR), all of the following functions must also be operating up to some minimum performance level:
______________________________________ Mobile and Cell Power Control Inter-Face Soft Handoff Inter-Cell Soft Handoff Inter-System Soft Handoff ______________________________________
To compound the problem,each of these is dependent upon many different software/hardware elements of the cellular system. Together they utilize large segments of the cell site hardware/software as well as the switch hardware/ software. In the case of Inter-System operations, the network between systems is also involved.
From the foregoing it is evident that whenever any of these system elements are upgraded or changed, there is a need for the Operating Company and the system Infrastructure Provider to verify that the changed system is able to provide the required QCR. This is a unique problem to CDMA systems, since they are necessarily reliant upon a smooth and effective meshing of all system elements so that the entire system operates in a manner which produces the required QCR. Also, it imposes a heavy burden on any test as well as maintenance system. For example, if a CDMA system is tested without loading the system with traffic, the coverage and quality may be verified but the capacity cannot. Conversely, if there is a test for capacity and quality but not for coverage, the coverage may not meet requirements. Since all three of these requirements are multivariate and interrelated and since all elements of the cellular hardware, in particular those in the CDMA system, must work well together, any change in any system element will impact the QCR and therefore the K-factor.
The limitations which have been discussed in the industry to date have been centered on the applicable theory, which is well known. For example, the maximum theoretical capacity is determined by the number of orthogonal Walsh (identifier) codes which are available in the system. In the present CDMA system, the maximum number of the Walsh codes is 64. However, of that number approximately seven codes must be used for other system functions. The reduced number of orthogonal codes at least theoretically indicates how much load or traffic can be carried, i.e., the capacity. However, it is also known that in actual system implementation the results are less. On the other hand it is not presently feasible to readily determine or predict how much less. Nor are there mechanisms available for quick and efficient determination of the overall effect of a change, so that the operation of the system is not perceptibly degraded.
Currently cellular operators make major system hardware/software changes late at night or early in the morning during minimum traffic hours. At that time the system is tested by making test calls and verifying that originations, terminations and hand-offs are working. In general, there is good assurance that if this works for 6-7 simultaneous calls, it will work when the system is under full load the following day. That is because coverage, quality and range are not interrelated within the system software/hardware.
However, in the case of IS-95 CDMA, verifying the performance of the system with a small number of phones located nearby the cell, or testing a phone or two in soft-handoff, fails to test the system under adequate load. Thus this test approach provides no assurance that the system will handle the normal system traffic nor does it assure any kind of system optimization. The result is that later in the day, when the peak loads occur, the system may severely degrade or even fail. In such a scenario the new software/hardware would have to be readjusted or replaced with the previous software/hardware during the peak load period, which is not advisable from an operational point of view. This approach would likely result in the system or some subset of cells becoming unavailable and perhaps produce a catastrophic failure. In the case where analog and CDMA systems co-exist in the same cell, it is possible that the analog service also would be affected and become unavailable.
In a different scenario of conventional testing, it is feasible to have 100-200 mobile unit operators make calls and travel within and between the cells and cell faces. However, this approach obviously involves significant expense and is very difficult to implement and duplicate to obtain satisfactory and unambiguous results.
Consequently, from the foregoing it can be seen that there is a critical need for a CDMA system testing and optimization procedure that is primarily effective, efficient, and of reasonably low cost. Further,the system and methodology should be subject to easy duplication and produce results which lend themselves to accurate comparison with the results of previous tests.